2018 ◽  
pp. 16-20
Author(s):  
Fred Pyrczak ◽  
Deborah M. Oh

2020 ◽  
pp. 46-48
Author(s):  
Louis Narens ◽  
Brian Skyrms

A quick introduction to scales of measurement, ordinal, interval, ratio, and absolute, and related issues of meaningfulness as invariance.


2017 ◽  
pp. 207-209
Author(s):  
Mildred L. Patten ◽  
Michelle Newhart

1986 ◽  
Vol 8 (3) ◽  
pp. 92-93
Author(s):  
H. Dahl ◽  
Jeffrey Dodgson

2020 ◽  
Vol 10 (2) ◽  
pp. 76-94
Author(s):  
M. A. Thomas

In the early 1900s, physics was the archetypical science and measurement was equated with mathematization to real numbers. To enable the use of mathematics to draw empirical conclusions about psychological data, which was often ordinal, Stevens redefined measurement as “the assignment of numerals to objects and events according to a rule.” He defined four scales of measurement (nominal, ordinal, interval, and ratio) and set out criteria for the permissible statistical tests to be used with each. Stevens' scales of measurement are still widely used in data analysis in the social sciences. They were revolutionary but flawed, leading to ongoing debate about the permissibility of the use of different statistical tests on different scales of data. Stevens implicitly assumed measurement involved mapping to real numbers. Rather than rely on Stevens' scales, researchers should demonstrate the mathematical properties of their data and map to analogous number sets, making claims regarding mathematization explicit, defending them with evidence, and using only those operations that are defined for that set.


2017 ◽  
Vol 15 (3) ◽  
pp. 189 ◽  
Author(s):  
Daniel Hahn, MA, MBA ◽  
Tierra L. Willis, MA ◽  
A. Ruthie Christie, MA ◽  
Samuel R. Mathews, PhD

Objective: To examine the relationship between social capital and potential resilience at the individual level from the perspective of emergency management.Methods: The authors used an online survey tool to present various scales of measurement related to the variables of social capital and potential resilience. Results: It was predicted that social capital and demographics, such as income, would be positively related to potential resilience. Overall, results indicated that income (β = 0.33, p < 0.01) and social capital (β = 0.32, p < 0.01) were both significant predictors of potential resilience. Implications and future directions for research and practices are discussed.


2009 ◽  
Vol 14 (2) ◽  
pp. 126-149 ◽  
Author(s):  
John J. McArdle ◽  
Kevin J. Grimm ◽  
Fumiaki Hamagami ◽  
Ryan P. Bowles ◽  
William Meredith

2014 ◽  
Vol 4 (1) ◽  
pp. 9 ◽  
Author(s):  
Jitsuki Sawamura ◽  
Shigeru Morishita ◽  
Jun Ishigooka

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